NYU CUSSL
E5 series (e.g., `intfloat/e5-large-v2`)
Strong, open-source embeddings for semantic search.
Excellent performance on MTEB benchmarkOpen-source and accessibleGood for retrieval tasksVarious model sizes available
Today's score
88.0
Where it ranks today
Best for / Not great for
Best for
- Semantic search engines
- RAG implementation
- Document retrieval
- Academic and research applications
Not great for
- Highly specialized classification tasks without fine-tuning
- Users preferring fully managed, high-touch enterprise solutions
- Real-time conversational AI requiring very fast re-ranking
Why it ranks here
The E5 model series remains a benchmark for open-source embeddings, consistently achieving top scores on retrieval benchmarks like MTEB. Its accessibility and strong performance make it a go-to for many RAG and semantic search projects.
30-day trend
Score breakdown
Search trends90
Benchmarks91
Developer buzz89
News mentions85
Pricing
API: $0.00 in · $0.00 out per 1M tokens · Consumer: $0.00/mo
Pricing plans
Popular
Open Source
Deploy E5 models yourself.
Free
- Downloadable weights
- Multiple model sizes
- Full customizability
- Requires self-hosting
API Access (Example)
Use E5 via managed APIs.
$0 /usage
- Pay-per-token
- Managed service
- Simple integration
- Scalable inference